DeepMind Technologies Limited, a UK subsidiary of Alphabet Inc, launched DeepMind Health a year ago, a venture to bring deep learning based AI technology to the healthcare space. DeepMind Health started a collaboration with the National Health Service of UK to apply its technology to the improvement of healthcare delivery.

As Mustafa Suleyman, a co-founder of DeepMind, describes in a blog post, some of NHS’s leading kidney specialists approached DeepMind in 2015 about the possibility of using technology to detect Acute Kidney Injury (AKI) at an early stage. Early detection of AKI has the potential to prevent a quarter of the annual 40,000 AKI deaths in the UK. Their first collaboration resulted in a mobile app that could get critical information about AKI patients quickly to nurses and doctors.

Last month DeepMind announced the first deployment of a secure clinical app called Streams that is designed to get the right information to the right clinician at the right time, and thereby improve the level of care that can be delivered with the same resources. DeepMind claims that the health practitioners reacted positively to the deployment. They are now planning for the second deployment of Streams to a healthcare facility. Although Streams certainly sounds like a successful and useful technology, it can hardly be called an AI deployment. However, other DeepMind research projects that are still at the research stage does involve the use of AI to solve clinical problems.

One such project involves the use of eye scans for diagnosis. Doctors use digital scans of the eye to diagnose and determine the correct treatment for common eye conditions such as age-related macular degeneration and diabetic retinopathy. DeepMind’s research is aimed at using AI to better analyse these scans, leading to earlier detection and treatment for patients and eventually help to avoid cases of preventable sight loss.

Another project uses machine learning to aid cancer treatment. Radiotherapy used to treat oral cancer and head and neck cancers has to be carefully planned, in order to ensure that no healthy structures are damaged. This planning process is called segmentation, and it involves producing a detailed map of the area to be treated, and isolating cancerous tissue from healthy tissue. The DeepMind project investigates whether deep learning could speed up the segmentation process while maintaining its accuracy.

Machine learning technology can analyse medical data and find ways to improve the diagnosis and treatment of illnesses. The initiative by DeepMind represents only the initial baby steps in this direction, but in the years to come this is likely to become one of the most important application domains of machine and deep learning.